1. Field of the Invention
The invention relates to imaging systems in environments having moving structures, and more particularly, to imaging systems and methods for detecting obstacles.
2. Related Art
Imaging systems are used in moving structures such as vehicles and motorized machines that involve navigation (such as robotic navigation or a conveying mechanism) to detect obstacles that may obstruct the desired motion. Such imaging systems typically use one or more cameras aimed at the path of motion and an image processing system that analyzes the captured images to detect obstacles. When an obstacle is detected, an alarm or other suitable notification may be communicated to allow for avoidance of the obstacle. Obstacle detection systems operate by detecting patterns in the image that are indicative of obstacles. Obstacle detection may be difficult where a structure is moving and suitable results often require the use of hardware and software equipment that may make obstacle detection too costly in the desired application.
One example of an obstacle detection system uses a stereo camera arrangement (a right camera and a left camera) to record images. The images from the cameras are processed using stereo inverse perspective mapping (IPM) to produce a difference image representing the difference between the left and right image. Stereo IPM used in an application for a vehicle may effectively filter out the road texture, road markings, and shadows that typically appear as planar objects on the road surface since images are captured synchronously by the left camera and the right camera. A binary image is obtained by performing some filter and labeling on the difference image. The binary image may contain some blobs, which may or may not be reliable obstacle objects. A polar histogram is computed for each blob and the peaks are analyzed. The strong peaks of the polar histogram may be interpreted as identifying obstacles. Although effective, stereo IPM requires the use of two cameras, which increases costs in an implementation. As a practical matter, applications that use stereo IPM obstacle detection must also factor in the need for space and proper placement of a second camera.
Another example detection system uses one camera in a moving car and also adopts an IPM image (top view). The monocular camera obtains one frame at any given time T and captures two frames between some time intervals to obtain two images that may be used to produce the IPM difference image. Because of vehicle movement, planar objects on the road surface, such as text painted on the road, road markers and shadows, will produce false positives. In order to reject such false positives, the monocular camera system identifies landmarks (such as lane marks) or objects representing prominent road texture in the road environment and uses these objects to compute car movement used to register two images. In another example of a monocular camera based obstacle detection system, optical flow is used to compute the motion parameters of the vehicles.
The monocular camera obstacle detection systems are able to detect obstacles using only one camera. However, such systems typically need to compute vehicle motion and motion parameters in order to register images. The added computation may be sufficiently complex to slow the system down making it difficult to detect obstacles in an effective timeframe.
A need exists for an obstacle detection system that does not require more than one camera and does not require computation of vehicle motion parameters.